rw-integrate-image

// Node.js SDK
import RunwayML from '@runwayml/sdk';
 
const client = new RunwayML();
 
const task = await client.textToImage.create({
  model: 'gen4_image',
  promptText: 'A serene Japanese garden with cherry blossoms and a koi pond',
  ratio: '1280:720'
}).waitForTaskOutput();
 
const imageUrl = task.output[0];

# Python SDK
from runwayml import RunwayML
 
client = RunwayML()
 
task = client.text_to_image.create(
    model='gen4_image',
    prompt_text='A serene Japanese garden with cherry blossoms and a koi pond',
    ratio='1280:720'
).wait_for_task_output()
 
image_url = task.output[0]

import fs from 'fs';
 
const refUpload = await client.uploads.createEphemeral(
  fs.createReadStream('/path/to/reference.jpg')
);
 
const task = await client.textToImage.create({
  model: 'gen4_image',
  promptText: 'A portrait in the style of @Reference',
  referenceImages: [
    { uri: refUpload.runwayUri, tag: 'Reference' }
  ],
  ratio: '1280:720'
}).waitForTaskOutput();

const task = await client.textToImage.create({
  model: 'gen4_image',
  promptText: '@EiffelTower painted in the style of @StarryNight',
  referenceImages: [
    { uri: 'https://cdn.yourapp.com/eiffel-tower.jpg', tag: 'EiffelTower' },
    { uri: 'https://cdn.yourapp.com/starry-night.jpg', tag: 'StarryNight' }
  ],
  ratio: '1280:720'
}).waitForTaskOutput();

task = client.text_to_image.create(
    model='gen4_image',
    prompt_text='@EiffelTower painted in the style of @StarryNight',
    reference_images=[
        {"uri": "https://cdn.yourapp.com/eiffel-tower.jpg", "tag": "EiffelTower"},
        {"uri": "https://cdn.yourapp.com/starry-night.jpg", "tag": "StarryNight"}
    ],
    ratio='1280:720'
).wait_for_task_output()

import RunwayML from '@runwayml/sdk';
import express from 'express';
 
const client = new RunwayML();
const app = express();
app.use(express.json());
 
// `runway://` URIs bypass this check; external URLs must match the allowlist.
const ALLOWED_MEDIA_HOSTS = new Set(['cdn.yourapp.com', 'uploads.yourapp.com']);
 
function validateReferenceImages(refs) {
  if (!Array.isArray(refs)) throw new Error('referenceImages must be an array');
  return refs.map(({ uri, tag }) => {
    if (typeof uri !== 'string' || typeof tag !== 'string') {
      throw new Error('each reference needs a uri and tag');
    }
    if (uri.startsWith('runway://')) return { uri, tag };
    const u = new URL(uri);
    if (u.protocol !== 'https:') throw new Error('https required');
    if (!ALLOWED_MEDIA_HOSTS.has(u.hostname)) throw new Error('untrusted media host');
    return { uri: u.toString(), tag };
  });
}
 
app.post('/api/generate-image', async (req, res) => {
  try {
    const { prompt, model = 'gen4_image', ratio = '1280:720', referenceImages } = req.body;
 
    const task = await client.textToImage.create({
      model,
      promptText: prompt,
      ratio,
      ...(referenceImages && { referenceImages: validateReferenceImages(referenceImages) })
    }).waitForTaskOutput();
 
    res.json({ imageUrl: task.output[0] });
  } catch (error) {
    console.error('Image generation failed:', error);
    res.status(400).json({ error: error.message });
  }
});

// app/api/generate-image/route.ts
import RunwayML from '@runwayml/sdk';
import { NextRequest, NextResponse } from 'next/server';
 
const client = new RunwayML();
 
export async function POST(request: NextRequest) {
  const { prompt, referenceImages } = await request.json();
 
  try {
    const task = await client.textToImage.create({
      model: 'gen4_image',
      promptText: prompt,
      ratio: '1280:720',
      ...(referenceImages && { referenceImages })
    }).waitForTaskOutput();
 
    return NextResponse.json({ imageUrl: task.output[0] });
  } catch (error) {
    return NextResponse.json(
      { error: error instanceof Error ? error.message : 'Generation failed' },
      { status: 500 }
    );
  }
}

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
from runwayml import RunwayML
 
app = FastAPI()
client = RunwayML()
 
class ImageRequest(BaseModel):
    prompt: str
    model: str = "gen4_image"
    ratio: str = "1280:720"
    reference_images: list[dict] | None = None
 
@app.post("/api/generate-image")
async def generate_image(req: ImageRequest):
    try:
        params = {
            "model": req.model,
            "prompt_text": req.prompt,
            "ratio": req.ratio,
        }
        if req.reference_images:
            params["reference_images"] = req.reference_images
 
        task = client.text_to_image.create(**params).wait_for_task_output()
        return {"image_url": task.output[0]}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))